BIP Exploring Ethical, Effective and Efficient Uses of AI to Support Health and Social Sciences Researchers

UniversityINGENIUM European University
Field of StudyEducation
Description

The aim of the BIP is to combine different disciplinary experiences and backgrounds from students and staff at the partner institutions to identify and address common questions around ethical, effective and efficient aspects of AI uses for researchers in Health and Social Sciences.

Format of Learning Material

Video, Audio, Pdf, Power point, etc

InstructorAndrea Bickerdike, Shannon Burke, Con Burns, Corina Cîmpanu, Joao Costa, Elena Drăgoi, Elisaveta Geretto, Todor Kondurdzhiev, Nikoleta Leventi, Jim O'Mahony, JOSE RAMON QUEVEDO PEREZ, Claire Walsh
Target Group
Type of LearningBlended
Keywords / TagsAcademic Integrity, AI, Health, Research, Social Sciences
Learning Outcomes

The Learning Outcomes focus on developing the participants' awareness, understanding, application and judgement of:

  1. ethical principles and boundaries of collecting, analysing and reporting data on different types of quantitative and qualitative data relative to Health and Social Sciences disciplines (e.g. biological markers, psychological dispositions, vital parameters, demographic features);
  2. validity requirements for collecting, analysing and reporting data leveraging on effective uses of AI;
  3. types, trade-offs and gains of efficiency in collecting, analysing and reporting data with AI tools;
  4. integration and interaction of AI tools with other digital tools and environments in relation to collection, analysis and reporting data in Health and Social Sciences.
Contents and Methods

This BIP includes an online component and an in-person component. The online component entails an introductory session (before the in-person week) and a concluding section (after the in-person week). These sessions will be delivered via Microsoft Teams.

During the in-person component, participants will experience:

  • Interactive Lectures and Workshops featuring exploring digital technologies, brainstorming activities, experience sharing, case studies, and live demonstrations.
  • Interdisciplinary and intercultural learning groups combining learning experience and expertise from different disciplines and levels of AI knowledge.

The BIP will be managed through the INGENIUM Moodle LMS, where all resources will be uploaded and assignments will be submitted.

Type of Assessment

Group Portfolio and Presentation

Study Materials
Prerequisites to Enrol
Type of Credentialcredits
ECTS3
Registrationhttps://elearn.ingenium-university.eu/enrol/index.php?id=90
Contact Details

joao.costa@mtu.ie

Number of Study Places25
ISCED